Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks by Lingyun Li, Jie Zhou, Demin Li, Jinde Cao, Xiaolu Zhang

“…We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. …”
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Influence of the type of load graphs on the service life transformers 33/11 Kv at substation "Kabun-1" (Syrian Arab Republic) by E. Yu. Abdullazyanov, E. I. Gracheva, A. Alzakkar, S. Valtchev, N. Mestnikov

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PM2.5 prediction and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration using spatial temporal graph convolutional networks by Yawen Zhao

“…To address this, this study uses spatiotemporal analysis and Spatial Temporal Graph Convolutional Networks (ST-GCN) to evaluate the variation and driving factors of PM _2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2014 to 2024, and to make predictions. …”
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The Spatial Pattern and Influencing Factors of the Intercity Real Estate Investment Network in the Yangtze River Delta by Dai Liang, Lyu Yifan, Zheng Huibin, Li Luqi

“…Next, this study explored how urban attribute, intercity dyadic, and endogenous structural factors influence the intercity investment network using exponential random graph models. …”
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Feature representation ‎via‎ graph-regularized ‎entropy-‎weighted nonnegative matrix factorization by Hazhir Sohrabi, Shahrokh Esmaeili, Parham Moradi

“…To address this challenge, this paper introduces Graph-Regularized Entropy-Weighted Nonnegative Matrix Factorization (GEWNMF) for enhanced feature representation. …”
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Traffic flow prediction based on spatial-temporal multi factor fusion graph convolutional networks by Ying-Ting Chen, An Liu, Cheng Li, Shuang Li, Xiao Yang

“…To address the above issues, we proposed a spatial-temporal multi factor fusion graph convolution network (STFGCN), which is composed of multi factor graph fusion module, the GCN based on the auto-regressive moving average (ARMA) filter and the gated recurrent unit (GRU). …”
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Wind Power Forecasting Based on Multi-Graph Neural Networks Considering External Disturbances by Xiaoyin Xu, Zhumei Luo, Menglong Feng

“…This paper introduces a novel framework GCN-EIF that decouples external interference factors (EIFs) from inherent wind power patterns to achieve excellent prediction accuracy. …”
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A comprehensive analysis of digital inclusive finance’s influence on high quality enterprise development through fixed effects and deep learning frameworks by Dedai Wei, Zimo Wang, Hanfu Kang, Xinye Sha, Yiran Xie, Anqi Dai, Kaichen Ouyang

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Global agricultural trade network characteristics and its influencing factors by Junwen Cao, Qingya Lei

“…Abstract This study investigates the evolutionary process of the global agricultural trade network and identifies key influencing factors. Utilizing social network analysis, a trade network model was constructed based on international trade data for six categories of agricultural products from 2013 to 2022. …”
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Forecasting Groundwater Level by Characterizing Multiple Spatial Dependencies of Environmental Factors Using Graph‐Based Deep Learning by Yinghan Wu, Gang Mei, Kaixuan Shao, Nengxiong Xu, Jianbing Peng

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Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study. by Robert W Gregg, Chad M Karoleski, Edwin K Silverman, Frank C Sciurba, Dawn L DeMeo, Panayiotis V Benos

“…<h4>Background</h4>Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. …”
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MODELING THE SYSTEM OF FACTORS INFLUENCING THE INTERNATIONAL COMPETITIVENESS OF UKRAINE’S ICT SECTOR by Єлизавета Завгородня, Ярослав Шестак

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A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…To solve this problem, we propose a feature extraction method named graph regularized non-negative matrix factorization with optimal estimation (GNMF-OE) according to the characteristics of well logging data in this paper. …”
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Metro Traffic Flow Prediction via Knowledge Graph and Spatiotemporal Graph Neural Network by Shun Wang, Yimei Lv, Yuan Peng, Xinglin Piao, Yong Zhang

“…Through the knowledge graph representation learning technology, we can learn the influence representation of external factors from the traffic knowledge graph, which can better incorporate the influence of external factors into the prediction model based on the spatiotemporal graph neural network. …”
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Influence of low-voltage electrical switching and protecting devices and parameters of electrical equipment on electricity losses in workshop power supply networks by E. Yu. Abdullazyanov, E. I. Gracheva, A. N. Gorlov, Z. M. Shakurova, A. G. Logacheva

“…To develop an algorithm for estimating electricity losses, taking into account the influencing factors in the main circuits of shop power supply. …”
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The influence of urban environment factors on the growth of horse chestnut Aesculus Hippocastanum L. by Szymon Józef Łukasiewicz

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Analysis of some factors influencing the performance of college students: An example of Computer Science education by L. V. Gubina, T. V. Alekseeva, O. A. Strakhov

“…In order to manage students’ education more effectively, among other measures, it is necessary to diagnose the motivation of enrolled students at the stage of admission to the educational institution and to identify the degree of awareness of their future career choice, as these factors directly depend on the success of educational programmes.The aim of the article was to reveal the trends of influence of students’ results at the Basic State Exam (OGE – the exam, which is taken when finishing education in the 9th (final) form of comprehensive school) on the level of knowledge of Computer Science in colleges and to find out the subjective reasons of students’ preferences for the secondary vocational education system to continue studies and to enter a profession.Methodology and research methods. …”
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A transient stability assessment method using quantitative analysis of key influencing factors and HGNN by YANG Kaixuan, LU Guoqiang, FU Guobin, ZHANG Wenzhao, LIU Lijun, LI Xing

“…In current research on transient stability assessment， the absence of quantitative analysis of key influencing factors hampers the accuracy of assessment results. …”
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Attitudes of nurses toward telenursing and influencing factors in resource-limited settings: Northwest Ethiopia 2022 by Fikadu Wake Butta, Biniyam Chaklu Tilahun, Berhanu Fikadie Endehabtu, Adamu Ambachew Shibabaw, Alex Ayenew Chereka, Ayenew Sisay Gebeyew, Mekides Molla Reda, Gemeda Wakgari Kitil, Teshome Demis Nimani

“…Descriptive statistics, including tables and bar graphs, were utilized. Additionally, a binary logistic regression analysis was conducted with 95% confidence intervals and a significance level of P &lt; 0.05 to identify factors influencing nurses' attitudes toward telenursing.ResultOut of the total 416 nurses who responded, representing a response rate of 98.35%, 39.7% exhibited favorable attitudes towards telenursing care. …”
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The Effect of High-voltage Pulse Potential Applied to the Substrate on the Phase Composition and Structure of the Vacuum-arc TiN Coatings by O.V. Sobol, N.V. Pinchuk, A.A. Andreev

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